In this section, we will introduce a representative visual self-supervised learning method that achieves supervised learning performance: \(\dagger \)  a simple framework for contrastive learning of visual representations (SimCLR) [1]} SimCLR is the main artifact in this subsection.. After that, we will discuss a few vicinal risk minimization (VRM) techniques that improve contrastive learning performance.
